﻿* Encoding: UTF-8.

/* Jones, Calvert W. 
/* "Does Interacting with Women Encourage Civic and Prosocial Attitudes? 
/*   Evidence from Simulated Contact Experiments in Saudi Arabia and Kuwait"
    

VALUE LABELS
treatment
1 "Interaction with Woman"
2 "Interaction with Man".
Execute.


VALUE LABELS
income
1 "very poor"
2 ""
3 ""
4 "middle class"
5 ""
6 ""
7 "Very rich".
Execute.

VALUE LABELS
relig
1 "Religiious"
2 "Religious to an extent"
3 "Not religious".
Execute.

IF  (govben  = 1) govben_r = 7.
EXECUTE.
IF  (govben  = 2) govben_r = 6.
EXECUTE.
IF  (govben  = 3) govben_r = 5.
EXECUTE.
IF  (govben  = 4) govben_r = 4.
EXECUTE.
IF  (govben  = 5) govben_r = 3.
EXECUTE.
IF  (govben  = 6) govben_r = 2.
EXECUTE.
IF  (govben  = 7) govben_r = 1.
EXECUTE.


IF  (bribe  = 1) bribe_r = 7.
EXECUTE.
IF  (bribe  = 2) bribe_r = 6.
EXECUTE.
IF  (bribe  = 3) bribe_r = 5.
EXECUTE.
IF  (bribe  = 4) bribe_r = 4.
EXECUTE.
IF  (bribe  = 5) bribe_r = 3.
EXECUTE.
IF  (bribe  = 6) bribe_r = 2.
EXECUTE.
IF  (bribe  = 7) bribe_r = 1.
EXECUTE.


IF  (speed  = 1) speed_r = 7.
EXECUTE.
IF  (speed  = 2) speed_r = 6.
EXECUTE.
IF  (speed  = 3) speed_r = 5.
EXECUTE.
IF  (speed  = 4) speed_r = 4.
EXECUTE.
IF  (speed  = 5) speed_r = 3.
EXECUTE.
IF  (speed  = 6) speed_r = 2.
EXECUTE.
IF  (speed  = 7) speed_r = 1.
EXECUTE.


IF  (exagres  = 1) exagres_r = 7.
EXECUTE.
IF  (exagres  = 2) exagres_r = 6.
EXECUTE.
IF  (exagres  = 3) exagres_r = 5.
EXECUTE.
IF  (exagres  = 4) exagres_r = 4.
EXECUTE.
IF  (exagres  = 5) exagres_r = 3.
EXECUTE.
IF  (exagres  = 6) exagres_r = 2.
EXECUTE.
IF  (exagres  = 7) exagres_r = 1.
EXECUTE.


IF  (hirefamily  = 1) hirefamily_r = 7.
EXECUTE.
IF  (hirefamily  = 2) hirefamily_r = 6.
EXECUTE.
IF  (hirefamily  = 3) hirefamily_r = 5.
EXECUTE.
IF  (hirefamily  = 4) hirefamily_r = 4.
EXECUTE.
IF  (hirefamily  = 5) hirefamily_r = 3.
EXECUTE.
IF  (hirefamily  = 6) hirefamily_r = 2.
EXECUTE.
IF  (hirefamily  = 7) hirefamily_r = 1.
EXECUTE.



/*reverse scoring tolerance


IF  (o_onecorrect  = 1) o_r_onecorrect = 7.
EXECUTE.
IF  (o_onecorrect  = 2) o_r_onecorrect = 6.
EXECUTE.
IF  (o_onecorrect  = 3) o_r_onecorrect = 5.
EXECUTE.
IF  (o_onecorrect  = 4) o_r_onecorrect = 4.
EXECUTE.
IF  (o_onecorrect  = 5) o_r_onecorrect = 3.
EXECUTE.
IF  (o_onecorrect  = 6) o_r_onecorrect = 2.
EXECUTE.
IF  (o_onecorrect  = 7) o_r_onecorrect = 1.
EXECUTE.


/* reverse score tolerance item  -- 'I prefer spending time with people of my own nationality.'

IF  (q7b  = 1) q7b_r = 7.
EXECUTE.
IF  (q7b  = 2) q7b_r = 6.
EXECUTE.
IF  (q7b  = 3) q7b_r = 5.
EXECUTE.
IF  (q7b  = 4) q7b_r = 4.
EXECUTE.
IF  (q7b  = 5) q7b_r = 3.
EXECUTE.
IF  (q7b  = 6) q7b_r = 2.
EXECUTE.
IF  (q7b  = 7) q7b_r = 1.
EXECUTE.

/* compute rule following index

compute just_abceg_r=MEAN(govben_r,bribe_r,speed_r,exagres_r,hirefamily_r).


/* compute law abidingness index

COMPUTE just_bc_r = MEAN(bribe_r,speed_r).

/* compute open mindedness index

COMPUTE openmind_bd=MEAN(o_twosides,o_r_onecorrect).


/* compute gender equality index

COMPUTE women_ie=MEAN(w_improve,w_equalpay).

/*compute tolerance index q 7


/* compute tolerance index

COMPUTE tolerance_q7=MEAN(q7a, q7b_r, q7c, q7d).
EXECUTE.



variable labels
    o_onecorrect 'There is usuallly only one correct opionion about an issue.'
    o_twosides 'I believe there are two sides to every question, and try to look at both.'
    govben 'Taking government benefits that you do not need'
    bribe 'Accepting a bribe'
    speed 'Driving over the speed limit'
    exagres 'Exaggerating on your resume'
    hirefamily 'Hiring a family member for a position in business when another applicant is more qualified'
    q7a 'I enjoy living in a diverse community with people with different religious backgrounds.'
    q7b 'I prefer speind gtime with people of my own nationality.'
    q7c 'I like to hear different peoples views on political issues even when I do not agree'
    q7d 'I enjoy spending time with people from different ethnic backgrounds.'
    w_equalpay 'Men and women should have equal job opportunities, wages, and salaries.'
    w_improve 'In general, social and economic problems would improve if there were more women in government.'.      
Execute.

VARIABLE LABELS
    age 'Age'
    income 'Income'
    relig 'Religiosity'
    openmind_bd 'Openness'
    women_ie 'Egalitarianism'
    just_abceg_r 'Rule Following'
    just_bc_r 'Law-Abidingness (subset)'
    tolerance_q7 'Tolerance'.
Execute.
    
/* Table 1, in manuscript

/* Kuwait results on dependent variables

USE ALL. 
COMPUTE filter_$=(sitenumber = 1). 
VARIABLE LABELS filter_$ 'sitenumber = 1 (FILTER)'. 
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. 
FORMATS filter_$ (f1.0). 
FILTER BY filter_$. 
EXECUTE.


T-TEST GROUPS=treatment(1 2) 
  /MISSING=ANALYSIS 
  /VARIABLES=openmind_bd women_ie just_abceg_r just_bc_r 
  /ES DISPLAY(TRUE) 
  /CRITERIA=CI(.95).

/* KSA results on dependent variables

USE ALL. 
COMPUTE filter_$=(sitenumber = 2). 
VARIABLE LABELS filter_$ 'sitenumber = 2 (FILTER)'. 
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. 
FORMATS filter_$ (f1.0). 
FILTER BY filter_$. 
EXECUTE.

T-TEST GROUPS=treatment(1 2) 
  /MISSING=ANALYSIS 
  /VARIABLES=openmind_bd women_ie just_abceg_r just_bc_r tolerance_q7 
  /ES DISPLAY(TRUE) 
  /CRITERIA=CI(.95).




/* pooled results on dependent variables

USE ALL. 
EXECUTE.

T-TEST GROUPS=treatment(1 2) 
  /MISSING=ANALYSIS 
  /VARIABLES=openmind_bd women_ie just_abceg_r just_bc_r  
  /ES DISPLAY(TRUE) 
  /CRITERIA=CI(.95).



/* Table C1 Demographics by treatment conditions, by country and pooled

/* Kuwait    

USE ALL. 
COMPUTE filter_$=(sitenumber = 1). 
VARIABLE LABELS filter_$ 'sitenumber = 1 (FILTER)'. 
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. 
FORMATS filter_$ (f1.0). 
FILTER BY filter_$. 
EXECUTE.


T-TEST GROUPS=treatment(1 2) 
  /MISSING=ANALYSIS 
  /VARIABLES= age relig income
  /ES DISPLAY(TRUE) 
  /CRITERIA=CI(.95).

/* Saudi Arabia

USE ALL. 
COMPUTE filter_$=(sitenumber = 2). 
VARIABLE LABELS filter_$ 'sitenumber = 2 (FILTER)'. 
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. 
FORMATS filter_$ (f1.0). 
FILTER BY filter_$. 
EXECUTE.

T-TEST GROUPS=treatment(1 2) 
  /MISSING=ANALYSIS 
  /VARIABLES=age relig income 
  /ES DISPLAY(TRUE) 
  /CRITERIA=CI(.95).

/* Pooled
    
USE ALL.
EXECUTE.


T-TEST GROUPS=treatment(1 2) 
  /MISSING=ANALYSIS 
  /VARIABLES=age relig income 
  /ES DISPLAY(TRUE) 
  /CRITERIA=CI(.95).
    
/* Table C2. Demographics across samples
    
USE ALL.
EXECUTE.

T-TEST GROUPS=sitenumber(1 2) 
  /MISSING=ANALYSIS 
  /VARIABLES=age relig income 
  /ES DISPLAY(TRUE) 
  /CRITERIA=CI(.95).


/* Appendix D Evidence of Gender Stereotypes
    
/* D1 Mean ratings of gendered adjectives


USE ALL. 
COMPUTE filter_$=(sitenumber = 2). 
VARIABLE LABELS filter_$ 'sitenumber = 2 (FILTER)'. 
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. 
FORMATS filter_$ (f1.0). 
FILTER BY filter_$. 
EXECUTE.

DESCRIPTIVES VARIABLES=warm decisive truthful powerful 
  /STATISTICS=MEAN STDDEV MIN MAX SEMEAN.

GRAPH 
  /ERRORBAR(CI 95)=powerful truthful decisive warm 
  /MISSING=LISTWISE.


/* D2 Paired samples t-test

compute warm_truthful = mean(warm, truthful).
compute decisive_powerful = mean(decisive, powerful).


T-TEST PAIRS=warm_truthful WITH decisive_powerful (PAIRED) 
  /ES DISPLAY(TRUE) STANDARDIZER(SD) 
  /CRITERIA=CI(.9500) 
  /MISSING=ANALYSIS.


/* Appendix E. Additional Analysis on Interaction Effects
/* religiosity by treatment interaction


/* compute interaction term for religiosity

compute treat_relig=treatment * relig.
execute.

/* Kuwait
    
USE ALL. 
COMPUTE filter_$=(sitenumber = 1). 
VARIABLE LABELS filter_$ 'sitenumber = 1(FILTER)'. 
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. 
FORMATS filter_$ (f1.0). 
FILTER BY filter_$. 
EXECUTE.


REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT openmind_bd 
  /METHOD=ENTER treatment relig treat_relig.


REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT women_ie
  /METHOD=ENTER treatment relig treat_relig.


REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT just_abceg_r 
  /METHOD=ENTER treatment relig treat_relig.
    

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT just_bc_r 
  /METHOD=ENTER treatment relig treat_relig.


/* Saudi Arabia

USE ALL. 
COMPUTE filter_$=(sitenumber = 2). 
VARIABLE LABELS filter_$ 'sitenumber = 2(FILTER)'. 
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'. 
FORMATS filter_$ (f1.0). 
FILTER BY filter_$. 
EXECUTE.


REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT openmind_bd 
  /METHOD=ENTER treatment relig treat_relig.


REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT women_ie
  /METHOD=ENTER treatment relig treat_relig.


REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT just_abceg_r 
  /METHOD=ENTER treatment relig treat_relig.
    

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10)
  /NOORIGIN 
  /DEPENDENT just_bc_r 
  /METHOD=ENTER treatment relig treat_relig.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT tolerance_q7
  /METHOD=ENTER treatment relig treat_relig.


/* pooled
    
USE ALL. 
EXECUTE.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT openmind_bd 
  /METHOD=ENTER treatment relig treat_relig.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT women_ie 
  /METHOD=ENTER treatment relig treat_relig.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT just_abceg_r
  /METHOD=ENTER treatment relig treat_relig.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT just_bc_r 
  /METHOD=ENTER treatment relig treat_relig.

REGRESSION 
  /MISSING LISTWISE 
  /STATISTICS COEFF OUTS R ANOVA 
  /CRITERIA=PIN(.05) POUT(.10) 
  /NOORIGIN 
  /DEPENDENT tolerance_q7 
  /METHOD=ENTER treatment relig treat_relig.



